Application of Cuckoo Search Algorithm for Image Segmentation

Kaouter Labed; Hadria Fizazi; Habib Mahi

doi:10.15866/irease.v10i3.11894

Application of Cuckoo Search Algorithm for Image Segmentation

Kaouter Labed^(1*), Hadria Fizazi⁽²⁾, Habib Mahi⁽³⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/irease.v10i3.11894

Abstract

Image analysis has a large interest in remote sensing, it is used for extract pertinent information, and the segmentation is found at the bottom of each analysis. Image segmentation is also considered as one of the most difficult, critical and essential tasks in image processing. It determines the quality of the final analysis result. Image segmentation can be viewed as an optimization problem, Meta heuristic optimization methods and in particular bio-inspired methods are very used in image segmentation, they can be applied to any mono or multiobjective optimization problem. In this paper we present a meta heuristic approach based on Cuckoo Search Algorithm (CSA) for the purpose of solving the problem of image segmentation in general and in particularly the satellite images segmentation.
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Keywords

Cuckoo Search Algorithms; Image Segmentation; Bio-Inspired Algorithms; Remote Sensing

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